


import argparse
import logging
import sys
from unittest.mock import patch

import run_glue_deebert

from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow


logging.basicConfig(level=logging.DEBUG)

_SCREAMING_SNAKE_CASE     :					int      =       logging.getLogger()
def      UpperCAmelCase__		():



     """simple docstring"""






     snake_case											=							argparse.ArgumentParser()
     parser.add_argument('''-f'''							)
     snake_case											=							parser.parse_args()
     return args.f

class     A__   (       snake_case__      ):







    """simple docstring"""

    def 						a_     (			self       ):
         snake_case											=							logging.StreamHandler(sys.stdout       )
         logger.addHandler(__snake_case       )
    def 						a_     (			self     ,   __snake_case       ):
         snake_case											=							get_gpu_count()

         if n_gpu > 1:
              pass
              # XXX: doesn't quite work with n_gpu > 1 https://github.com/huggingface/transformers/issues/10560
              # script = f"{self.examples_dir_str}/research_projects/deebert/run_glue_deebert.py"
              # distributed_args = f"-m torch.distributed.launch --nproc_per_node={n_gpu} {script}".split()
              # cmd = [sys.executable] + distributed_args + args
              # execute_subprocess_async(cmd, env=self.get_env())
              # XXX: test the results - need to save them first into .json file
         else:
              args.insert(0     ,   '''run_glue_deebert.py'''       )
              with patch.object(__snake_case     ,   '''argv'''     ,   __snake_case       ):
                   snake_case											=							run_glue_deebert.main()
                   for value in result.values():
                        self.assertGreaterEqual(__snake_case     ,   0.666       )




    @slow
    @require_torch_non_multi_gpu
    def 						a_     (			self       ):
         snake_case											=							'''
            --model_type roberta
            --model_name_or_path roberta-base
            --task_name MRPC
            --do_train
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --max_seq_length 128
            --per_gpu_eval_batch_size=1
            --per_gpu_train_batch_size=8
            --learning_rate 2e-4
            --num_train_epochs 3
            --overwrite_output_dir
            --seed 42
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --save_steps 0
            --overwrite_cache
            --eval_after_first_stage
            '''.split()
         self.run_and_check(__snake_case       )

         snake_case											=							'''
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --eval_each_highway
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            '''.split()
         self.run_and_check(__snake_case       )

         snake_case											=							'''
            --model_type roberta
            --model_name_or_path ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --task_name MRPC
            --do_eval
            --do_lower_case
            --data_dir ./tests/fixtures/tests_samples/MRPC/
            --output_dir ./examples/deebert/saved_models/roberta-base/MRPC/two_stage
            --plot_data_dir ./examples/deebert/results/
            --max_seq_length 128
            --early_exit_entropy 0.1
            --eval_highway
            --overwrite_cache
            --per_gpu_eval_batch_size=1
            '''.split()
         self.run_and_check(__snake_case       )








class     A__   :







    """simple docstring"""

    def __init__(			self     ,   __snake_case       ):
         snake_case											=							n
         snake_case											=							[None] * self.n
         snake_case											=							0  # index of the first element
         snake_case											=							0
         snake_case											=							0
    def __len__(			self       ):
         return self.size
    def 						a_     (			self       ):
         return self.size == 0
    def 						a_     (			self       ):
         return False if self.is_empty() else self.array[self.front]
    def 						a_     (			self     ,   __snake_case       ):
         if self.size >= self.n:
              raise Exception('''QUEUE IS FULL'''       )

         snake_case											=							data
         snake_case											=							(self.rear + 1) % self.n
         self.size += 1
         return self




    def 						a_     (			self       ):
         if self.size == 0:
              raise Exception('''UNDERFLOW'''       )

         snake_case											=							self.array[self.front]
         snake_case											=							None
         snake_case											=							(self.front + 1) % self.n
         self.size -= 1
         return temp




